Pleco and Plectron - Two Provably Secure Password Hashing Algorithms.
Bibliographic record
Abstract
Password-based authentication has been widely deployed in practice due to its simplicity and efficiency. Storing pass-words and deriving cryptographic keys from passwords in a secure manner are crucial for many security systems and services. However, choices of well-studied password hashing algorithms are extremely limited, as their security require-ments and design principles are different from common cryp-tographic algorithms. In this paper, we propose two practi-cal password hashing algorithms, Pleco and Plectron. They are built upon well-understood cryptographic algo-rithms, and combine advantages of symmetric and asymmet-ric primitives. By employing the Rabin cryptosystem, we prove that the one-wayness of Pleco is at least as strong as the hard problem of integer factorization. In addition, both password hashing algorithms are designed to be sequential memory-hard, in order to thwart large-scale password crack-ing by parallel hardware, such as GPUs, FPGAs, and ASICs. Moreover, total computation and memory consumptions of Pleco and Plectron are tunable through their cost pa-rameters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".